Instructions to use Anirudh7003/roberta-base-rte-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Anirudh7003/roberta-base-rte-lora with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Anirudh7003/roberta-base-rte-lora")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Anirudh7003/roberta-base-rte-lora", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from Anirudh7003/roberta-base-rte-lora: direct link, hf CLI and curl.
- Browser
- Download file 405 Bytes
-
https://huggingface.co/Anirudh7003/roberta-base-rte-lora/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://Anirudh7003/roberta-base-rte-lora/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/Anirudh7003/roberta-base-rte-lora/resolve/main/tokenizer_config.json
405 Bytes
| { | |
| "add_prefix_space": false, | |
| "backend": "tokenizers", | |
| "bos_token": "<s>", | |
| "cls_token": "<s>", | |
| "eos_token": "</s>", | |
| "errors": "replace", | |
| "is_local": false, | |
| "local_files_only": false, | |
| "mask_token": "<mask>", | |
| "model_max_length": 512, | |
| "pad_token": "<pad>", | |
| "sep_token": "</s>", | |
| "tokenizer_class": "RobertaTokenizer", | |
| "trim_offsets": true, | |
| "unk_token": "<unk>" | |
| } | |